Power Cost Function Research Articles

Real-Time Tone-Mapping Processor with Integrated Photographic and Gradient Compression using 0.13 μm Technology on an Arm Soc Platform

Due to recent advances in high dynamic range (HDR) technologies, the ability to display HDR images or videos on conventional LCD devices has become more and more important. Many tone-mapping algorithms have been proposed to meet this end, the choice of which depends on display characteristics such as luminance range, contrast ratio and gamma correction. An ideal HDR tone-mapping processor should have a robust core functionality, high flexibility, and low area consumption, and therefore an ARM-core-based system-on-chip (SOC) platform with a HDR tone-mapping application-specific integrated circuit (ASIC) is suitable for such applications. In this paper, we present a systematic methodology for the development of a tone-mapping processor of optimized architecture using an ARM SOC platform, and illustrate the use of this novel HDR tone-mapping processor for both photographic and gradient compression. Optimization is achieved through four major steps: common module extraction, computation power enhancement, hardware/software partition, and cost function analysis. Based on the proposed scheme, we present an integrated photographic and gradient tone-mapping processor that can be configured for different applications. This newly-developed processor can process 1,024 × 768 images at 60 fps, runs at 100 MHz clock and consumes a core area of 8.1 mm2 under TSMC 0.13 μm technology, resulting in a 50% improvement in speed and area as compared with previously-described processors.

Social Welfare Maximization Considering Reactive Power and Congestion Management in the Deregulated Environment

This article addresses two well-known problems of competitive electricity markets: (1) reactive power procurement and (2) congestion management, using social welfare maximization in pool based competitive electricity markets. The social welfare function, which customarily consists of the benefit function of consumers and cost function of real power generation, is modified to include the cost function of reactive power generation. This will incorporate an economic signal regarding production and consumption of reactive power within locational marginal prices payable to the suppliers and chargeable from the consumers at different locations. The reactive power cost function of a synchronous generator is modeled using the lost opportunity to trade real power to produce required amount of reactive power. An approximate P-Q capability curve of the synchronous generator is used for this purpose. Further, the effect of incorporation of consumers' benefit bids on managing system congestion at an acceptable level is demonstrated with the help of decomposition of locational marginal prices of real and reactive power into energy/reference, loss, and congestion components. The effectiveness of the technique is tested on a 5-bus system and an IEEE 118-bus system. A discussion is presented to explain and compare the results obtained.

Optimal multilevel organizations for the power cost functions

The problem of maximizing the profit of an economic organization with simultaneous selection of its composition and structure was formulated. Consideration was given to a class of the power cost functions whose parameters reflect the organization environmental characteristics. The optimal organization was analytically established for this case, and the regularities of its variation vs. the environmental conditions were investigated.

An efficient and almost budget balanced cost sharing method

For a convex technology C we characterize cost sharing games where the Nash equilibrium demands maximize total surplus. Budget balance is possible if and only if C is polynomial of degree n − 1 or less. For general C, the residual * cost shares are balanced if at least one demand is null, a characteristic property. If the cost function is totally monotone, a null demand receives cash and total payments may exceed actual cost. The ratio of excess payment to efficient surplus is at most min { 2 log n , 1 } . For power cost functions, C ( a ) = a p , p > 1 , the ratio of budget imbalance to efficient surplus vanishes as 1 n p − 1 . For analytic cost functions, the ratio converges to zero exponentially along a given sequence of users. All asymptotic properties are lost if the cost function is not smooth.

Formulation of a tactical logistics decision analysis problem using an optimal control approach

In recent years, engineers, economists, and military commanders amongst others have placed increasing emphasis on decision making under conditions of uncertainty. Much of life involves making choices under uncertainty, that is, choosing from some set of alternative courses of action in situations where we are uncertain about the actual consequences that will occur for each course of action being considered. It is the field of Decision Analysis that is concerned with the making of rational, consistent decisions, notably under conditions of uncertainty. That is, Decision Analysis helps the decision maker to analyse a complex situation with many different alternatives, states and consequences and to choose the best alternative in light of the information available. The objective of Decision Analysis is to choose a course of action consistent with the basic preferences and knowledge of the decision maker. In this paper we investigate the problem of decision making for the direction of resources within a network of support. This network seeks to mimic how logistic support might be delivered in a military area of operations. It is shown that transitions in the state variables depend upon the status of the network at the end of the previous cycle, the physical distribution decisions taken in the current and previous cycle and the demand for support experienced in the current cycle. By using control theory we are able to formulate the above problem as an optimal control problem, that is, the state variables $X(t)$ are governed by a certain transition function $F$, and we are seeking the decision stream (optimal controller) for physical distribution actions such that a given Combat Power Cost function is optimised. This latter function is fashioned on some contemporary measures of effectiveness adopted for military logistics. Furthermore, the problem of decision making under uncertainty is also studied by using robust optimal control techniques to formulate the effects of changing situational awareness. A simple case study is given to show the potential of the proposed techniques.

Optimal controllability norm for the power cost function

Consideration was given to a model of the multilevel hierarchical structure controlling a "production line" (successive business process) where the manager's costs are defined by a power function depending on the intensity of the subprocess controlled by this manager. For the model under study, the optimal hierarchy of control was determined, and the dependence of the optimal controllability norm (the number of "deputies" of one manager) on the model parameters (for example, the power which may be interpreted as the degree of environmental instability) was analyzed.

Optimal setup time reduction for a single product with dynamic demands

We consider the problem or reducing setup times for the dynamic lot-sizing problem. We explicitly consider setup times and setup reduction costs. A dynamic programming procedure is proposed for solving the problem. Explicit expressions are given for the two types of setup reduction cost functions that are commonly studied in the setup reduction literature (the logarithmic and the power cost functions). A numerical example is provided.

TVA Hydro Scheduling Model: Theoretical Aspects

The optimization procedures used in the Tennessee Valley Authority (TVA) HYDROSIM model are described. Scheduling of the TVA operated reservoir system poses a stochastic, nonlinear, multireservoir problem with both nonviolable (physical) and violable (operating) constraints. A linear programming procedure for implementing the preemptive priority constraints and a nonlinear search procedure for minimizing the power cost function are described. A guide development program based on stochastic dynamic programming is also described.